Comparing high level MapReduce query languages

Stewart, R., Trinder, P.W. and Loidl, H.W. (2011) Comparing high level MapReduce query languages. In: Advanced Parallel Processing Technology Symposium (APPT'11), Shanghai, China, 26-27 Sep 2011,

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Abstract

The MapReduce parallel computational model is of increasing importance. A number of High Level Query Languages (HLQLs) have been constructed on top of the Hadoop MapReduce realization, primarily Pig, Hive, and JAQL. This paper makes a systematic performance comparison of these three HLQLs, focusing on scale up, scale out and runtime metrics. We further make a language comparison of the HLQLs focusing on conciseness and computational power. The HLQL development communities are engaged in the study, which revealed technical bottlenecks and limitations described in this document, and it is impacting their development.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Trinder, Professor Phil
Authors: Stewart, R., Trinder, P.W., and Loidl, H.W.
College/School:College of Science and Engineering > School of Computing Science

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